47-5022.00
Excavating and Loading Machine and Dragline Operators, Surface Mining
Operate or tend machinery at surface mining site, equipped with scoops, shovels, or buckets to excavate and load loose materials.
This role faces substantial AI disruption
More at risk than 68% of occupations we track
Disruption Vector
Physical Robots
Physical robotics, autonomous machines, and automated equipment are the main threat to the physical tasks in this occupation.
Excavating and Loading Machine Operators work surface mining equipment — physical operation roles where AI-assisted automation (autonomous haul trucks from Caterpillar and Komatsu) is advancing, particularly in large-scale open-pit mining. The mining sector is one of the leaders in autonomous equipment deployment, and operator roles face meaningful displacement pressure through 2027, particularly in large operations.
Salary & Job Outlook
AI Risk Timeline
Projection model: Based on current AI capability growth rates. High-risk occupations are projected to see compounding automation pressure, while human-centric roles show slower risk accumulation. These are statistical projections, not guarantees.
Skills Analysis — AI Vulnerability
Career Pivot Paths
If you're a Excavating and Loading Machine and Dragline Operators, Surface Mining, consider pivoting toward these lower-risk roles:
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Excavating and Loading Machine and Dragline Operators, Surface Mining
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I just checked if I'm cooked as a Excavating and Loading Machine and Dragline Operators, Surface Mining 🤖 AI risk score: 7.0/10 — High Risk "You're not cooked yet, but someone's preheating the oven." Check yours 👇 https://amicooked-five.vercel.app/results/47-5022.00 #AmICooked #AI #FutureOfWork
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You're more at risk than a Energy Engineers, Except Wind and Solar (score: 1.6). Maybe it's time to rethink.
This analysis is for informational purposes only and is based on statistical models and academic research. It does not constitute career advice and is not a guarantee of future employment outcomes. AI impact varies significantly by employer, region, and individual circumstances. Learn about our methodology →